Most of the bacteria in the NIAID Priority Pathogen list from all three Categories invade human cells and for many the only known reproductive stage of infection takes place in membrane-bound vacuoles or directly in the cytosol of these host cells. Almost all antibiotics, and all that are administered orally, act by blocking some metabolic pathway of rapidly growing bacteria rather than by disrupting the bacterial cell. Therefore, the identification of new targets for antibiotic action requires knowledge of the active metabolism of replicating intracellular (IC) bacteria. Predictive computer models of the metabolism of E. coli (a close relative to Shigella flexneri) have been constructed using Constraint-based Flux Balance Analysis (CFBA). The chemical constituents of rapidly growing E. coli cells have been determined, and this information was used in building the CFBA models. However, the equivalent information for eukaryotic cells, which is basically the growth medium for IC bacteria, is not as complete, and will be investigated. Knowledge of the constituents of eukaryotic cell cytosol is required to develop CFBA models to analyze the metabolism of bacteria during their IC replicative stage. S. flexneri, a Category B pathogen, will be used as: (Specific Aim 1) a biosensor to determine constituents of the cytosol of human-derived cells and (Specific Aim 2) the model organism for this innovative application of CFBA. Several attributes of S. flexneri make it a good choice to probe the eukaryotic cytosol for bacterially accessible compounds: replication in the cytosol (no vacuolar membrane to complicate the analysis), a large repertoire of uptake systems (to assess availability to bacteria of compounds in the cytosol) and genetic tools to examine heterologous uptake systems. CFBA translates a metabolic network (described as stoichiometric bio-chemical reactions) into an optimization problem with constraints on each molecule that the organism can exchange with its environment (in this case eukaryotic cytosol). A general model (to allow adaptation to different bacteria) will be constructed from the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic database. The S. flexneri CFBA model will be derived from the reference model using published reports of the genome and the IC behavior of S. flexneri mutants. Modeling the metabolism of NIAID Priority Pathogens will aid our understanding of a large number of potential bioterror agents and help direct the search for new antibacterial drugs. [unreadable] [unreadable]